Method and System for Analyzing a Blood Sample

ABSTRACT

Methods, systems, and computer program products for the analysis of a blood sample are disclosed. One embodiment is a method of detecting and enumerating hard-to-ghost cells in a blood sample. Another embodiments is a method of analyzing reticulocytes in a blood sample. Methods of using blood count parameters are also provided.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.12/730,977, filed Mar. 24, 2010, which is a continuation-in-part of U.S.application Ser. No. 12/234,275, filed on Sep. 19, 2008, now U.S. Pat.No. 8,512,977, all of which are incorporated herein by reference intheir entirety.

BACKGROUND

1. Field of the Invention

This invention relates in general to the methods and systems foranalyzing the blood samples using a particle analyzer, and moreparticularly to determining reticulocytes and hard-to-ghost cells.

2. Background

Each year, millions of Americans are affected by blood diseases.Examples of blood pathologies include various hematologicalmalignancies, such as leukemias and lymphomas, hemoglobinopathies, whichencompass a number of anemias of genetic origin, such as thalassemia,Cooley's Disease, and sickle-cell anemia (HbS disease), as well asvarious clotting and bleeding disorders. Blood abnormality can also be asecondary consequence associated with other conditions, such HIV/AIDS,malignant tumors, and autoimmune disorders. Most of these conditionshave significant morbidity and mortality and commonly cause severe painin the affected patient. Early diagnosis of these disorders is criticalso patients who have the disease can receive proper treatment anddisease management.

Blood is a specialized bodily fluid that delivers necessary substances,such as nutrients and oxygen, to the body's cells and transports wasteproducts away from those same cells. The predominant cell in blood isthe erythrocyte, i.e., red blood cell or red cell. In a peripheral bloodsmear, erythrocytes derive their reddish color from protein hemoglobin,and usually appear round or oval with a pale-staining center region.Their biconcave morphology increases the cell's surface area andfacilitates diffusion of oxygen and carbon dioxide from the cell. Atypical erythrocyte has a lifespan of about 120 days.

Erythrocytes develop from nucleated precursor cells in the bone marrow.Immature erythrocytes, i.e., reticulocytes, have organelles thatcontribute to an increased hemoglobin content and gas-carrying capacity.Reticulocytes can be recognized in peripheral blood smears when aspecial stain is used to stain their polyribosome or ribonucleic acid(RNA). Under typical conditions, reticulocytes account for about 1-2% ofred blood cells in a sample. However, during certain periods of physicalneed, the reticulocyte count may increase.

Blood tests can be used to determine physiological and biochemicalstates, such as disease, mineral content, drug effectiveness, and organfunction. In confirming or helping to confirm the diagnosis of diseasessuch as, for example, various forms of anemia or acute internalhemorrhage, the determination of reticulocytes can be of criticalimportance.

Automated reticulocyte analysis can be done using a particle analyzersuch as a flow cytometer or hematology analyzer. Example particleanalyzers include, the UniCel® D×H 800 System from Beckman Coulter andXT-2000 from Sysmex Corporation. The preparation of a blood sample forcytometric flow or hematology analysis generally involves taking a wholeblood sample and performing one or both the steps of incubating thesample of blood with a vital stain such as New Methylene Blue (NMB) anddiluting the blood sample with a hypotonic acid that clears hemoglobin.The staining precipitates RNA within the erythrocytes. Diluting with ahypotonic acid clears hemoglobin, leaving the stained RNA within thecells. The process of removing hemoglobin is commonly referred to as“ghosting.” The blood sample, or portion of it, is then subjected toanalysis in a flow cell of a particle analyzer. Typically, cells in asheath fluid pass through a point in the flow cell, one by one, wherethey are interrogated by one or more beams of light. Severalmeasurements are generated for each passing cell. The interrogation of asingle cell is referred to as a cell event. Commonly recordedmeasurements per cell event include, forward light scatter, axial lightloss, and fluorescence. Some particle analyzers also collect a directcurrent impedance (DC) measurement which is a measure of how muchimpedance is exerted by a cell. The DC measurement, which is obtainedfrom applying the maximum current such that the cell membrane is notpermeated and no current flows through the cell, is also known asCoulter volume or volume.

SUMMARY OF THE INVENTION

The present application is directed towards the analysis of particleanalyzer data. In one embodiment, an automated method of enumeratinghard-to-ghost cells in a blood cell sample can include: mixing a bloodcell sample with a nucleic acid stain and a ghosting reagent to removehemoglobin from red blood cells, thereby generating a ghosted blood cellsample; passing the ghosted blood cell sample through a cytometric flowcell; analyzing the ghosted blood cell sample in the cytometric flowcell by using two different optical measurements; differentiatinghard-to-ghost cells by detecting the two different optical measurements;and enumerating the hard-to-ghost cells.

In another embodiment a method of analyzing a blood sample can include:measuring the blood sample in a flow cell by a detection comprising anaxial light loss measurement to generate event data; identifying ahard-to-ghost cell population using the event data, based on the axiallight loss measurement; filtering-out the hard-to-ghost cell populationfrom said event data; and analyzing the event data to identify bloodcell distribution patterns. Analysis including the reticulocyte analysiscan be performed subsequent to filtering out the hard-to-ghost cells.

In some embodiments, a method of analyzing a blood sample can includethe steps of enumerating the population of hard-to-ghost cells using theevent data generated by axial light loss measurements. An example of anembodiment that is reported can be % hard-to-ghost cells of a total redblood cell population. Said value can be used as a research use only(RUO) parameter, or can be developed into an in vitro diagnostic (IVD)parameter.

In yet another embodiment, an automated method of enumeratinghard-to-ghost cells in a blood cell sample can include: mixing a bloodcell sample with a nucleic acid-staining fluorescent dye to stain theblood cells containing nucleic acid and a ghosting reagent to removehemoglobin from red blood cells in the blood cell sample, therebygenerating a ghosted blood cell sample; passing the ghosted blood cellsample through a cytometric flow cell; analyzing the ghosted blood cellsample in the cytometric flow cell by using light scatter andfluorescence measurements; differentiating hard-to-ghost cells from thefluorescently stained cells containing nucleic acid and ghosted cells bydetecting fluorescence and light scatter measurements; and enumeratingthe hard-to-ghost cells.

Further features and advantages of the present invention, as well as thestructure and operation of various embodiments thereof, are described indetail below with reference to the accompanying drawings. It is notedthat the invention is not limited to the specific embodiments describedherein. Such embodiments are presented herein for illustrative purposesonly. Additional embodiments will be apparent to persons skilled in therelevant art(s) based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a view of event data from analysis of a blood sample using aflow cytometer, in two-dimensions.

FIG. 2 illustrates steps in analyzing immature reticulocytes in a bloodsample according to an embodiment of the present invention.

FIG. 3 shows further details of the preprocessing step shown in FIG. 2,according to an embodiment of the present invention.

FIG. 4 shows further details of the measuring step shown in FIG. 2,according to an embodiment of the present invention.

FIG. 5(A) is a two-dimensional view of event data from the analysis of ablood sample.

FIG. 5(B) is a view of the event data shown in FIG. 5(A) with thehard-to-ghost cell population removed.

FIG. 6 shows the same event population shown in FIG. 5(A), but usingaxial light loss (ALL) and UMALS instead of the conventional DC andUMALS.

FIG. 7(A) shows a two-dimensional view of DC plotted against UMALSillustrating event data with the capability to identify thehard-to-ghost cell population.

FIG. 7(B) shows a two-dimensional view of ALL plotted against UMALSillustrating even data with the capability to identify the hard-to-ghostcell population.

FIG. 7(C) shows another two-dimensional view of DC plotted against UMALSillustrating event data with the capability to identify thehard-to-ghost cell population.

FIG. 8 shows further details of the measuring step shown in FIG. 2,according to another embodiment of the present invention.

FIG. 9 is a system for evaluating immature reticulocytes according to anembodiment of the present invention.

FIG. 10(A) shows a three-dimensional view of the event data from theanalysis of a blood sample from a healthy individual. Hard-to-ghostcells 1010, mature red blood cells 1020, and reticulocytes 1030 aredistinctly differentiated in the view.

FIG. 10(B) shows a three-dimensional view of the event data from theanalysis of a blood sample from a patient diagnosed with sickle cellanemia. Hard-to-ghost cells 1010, mature red blood cells 1020, andreticulocytes 1030 are distinctly differentiated in the view.

FIG. 10(C) shows a three-dimensional view of the event data from theanalysis of a blood sample from a patient diagnosed with Thalassemia.Hard-to-ghost cells 1010, mature red blood cells 1020, and reticulocytes1030 are distinctly differentiated in the view.

FIG. 11 illustrate an average % of “hard-to-ghost” cells in bloodsamples drawn from healthy individuals.

FIG. 12 illustrate an average % of “hard-to-ghost” cells in bloodsamples drawn from patients suffering from various diseases.

The features and advantages of the present invention will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings. In the drawings, like reference numbersgenerally indicate identical, functionally similar, and/or structurallysimilar elements. Generally, the drawing in which an element firstappears is indicated by the leftmost digit(s) in the correspondingreference number.

DETAILED DESCRIPTION

The present invention relates to particle analysis data processing.While the present invention is described herein with reference toillustrative embodiments for particular applications, it should beunderstood that the invention is not limited thereto. Those skilled inthe art with access to the teachings herein will recognize additionalmodifications, applications, and embodiments within the scope thereofand additional fields in which the invention would be of significantutility.

Overview

As described in the background section above, the automated ability todetermine the distribution of red blood cells in a blood sample is avital capability for several applications. The methods and systemsdisclosed herein yield an improved automated measure of cell populationsin a blood sample. In one embodiment, the hard-to-ghost cells aredifferentiated and enumerated using methods provided herein.

Exemplary environments in which this invention may be practiced includeparticle analyzers, such as Beckman Coulter's UniCel® D×H 800 System.The UniCel® D×H 800 System, for example, uses the Coulter proprietaryVolume, Conductivity, and LightScatter (VCS) technology to evaluatehydrodynamically focused cells within a flow cell. VCS uses threeindependent energy sources that work in concert with each other for cellmeasurement: a low frequency direct current power source to measurevolume; a high frequency power source to measure conductivity, and alaser light source to measure scatter. The volume measurement isperformed using the Coulter principle of electrical impedance tophysically measure the volume that the entire cell displaces in anisotonic diluent. This method accurately sizes all cell types regardlessof their orientation in the light path. Alternating current in the radiofrequency (RF) range short circuits the bipolar lipid layer of a cell'smembrane, allowing the energy to penetrate the cell. This powerfulmethod is used to collect information about cell size and internalstructure, including chemical composition and nuclear volume. A laserand multiple-angle light scatter detectors provide information about acell's internal structure, granularity, and surface morphology. Inaddition, VCS devices use the highly accurate DC measurement of volumeto obtain other measurements that are adjusted for cell size fromconductivity and scatter. U.S. Pat. No. 5,616,501 (to Rodriguez et al.),U.S. Pat. No. 6,060,322 (to Horton et al.), U.S. Pat. No. 6,410,330 (toLi et al.), and U.S. Pat. No. 6,472,215 (to Huo et al.), all of whichare hereby incorporated by reference in their entirety, describe the useof VCS technology with respect to detecting reticulocytes and otherreticulated cells. It should be noted, however, that the teachings inthis disclosure are not limited to devices using VCS technology.

FIG. 1 shows a two-dimensional scatter plot of a blood sample based onevent data generated from measurements of blood using a particleanalyzer. Each data point appearing in the scatter plot is based onselected measurements obtained from one cell event, i.e., theinterrogation of an individual cell by an electric current and a laserbeam in the flow cell. Event data populations of different cell typescommonly found in a blood sample are shown in the scatter plot. Ingeneral, sufficient separation exists between the populations of redcells as a whole (i.e., erythrocytes 102 and reticulocytes 104),platelets 108, and white cells 106, that known techniques allow forgating the red cell population as a whole, for example, based on thearea defined by lines 122 and 124. Gating refers to the process offiltering selected measurements from multi-parameter data, for example,as described above, separating red cells (erythrocytes andreticulocytes), platelets and white blood cells by testing themeasurements generated for each cell event against known thresholdvalues. For example, line 124 can be a threshold volume value and line122 can be a threshold light scatter value, where cell events withvolume measurements above line 124 and light scatter (often used in theform of log of light scatter) value less than line 122 correspond toeither erythrocytes or reticulocytes. In existing systems, thereticulocyte population can also be gated, for example, by a line suchas line 130. The events to the right of line 130 are reticulocytes,whereas the events to the left of line 130 are mature red cells.

Analyzing Reticulocytes

In one aspect, methods for analyzing reticulocytes in a blood sample arepresented. FIG. 2 is a flowchart of steps in evaluating reticulocytesaccording to an embodiment of the present invention. In step 202, ablood sample is prepared for analysis in a particle analyzer.Preparation can include ghosting the blood sample and/or staining thesample with a suitable dye or stain. FIG. 3 illustrates preparation step202 in further detail, according to one embodiment. In step 302, theblood sample can be combined with a vital stain to further delineatereticulocytes. For example, a non-fluorochrome dye that precipitatesintracellular ribonucleic acid (RNA) of the reticulocyte can be used.Examples of suitable stains include, but are not limited to, NewMethylene Blue (known as Reagent A of the Coulter Retic Pak™), Oxazine750, and Brilliant Cresyl Blue. RNA, having been precipitated, will havehigher density which will enhance the delineation of the RNA content ineach cell. Using a non-fluorescent dye to measure reticulocytes has theadded advantage to allow the blood sample to be further analyzed forother constituents by utilizing a fluorescent dye, if desired. Examplesof suitable fluorescent dyes include, but are not limited to, thiazoleorange and polymethine. Additional preparatory steps are possible invarious embodiments of the present invention. For example, in someembodiments a fluorescent dye can be combined with the blood sample tomeasure additional properties of the sample using a fluorescencemeasure.

To further effectuate the examination of a composition of a bloodsample, the blood sample can be combined with a reagent such as, forexample, a reticulocyte ghosting solution having potassium thiocyanateand sulfuric acid (step 304). This type of ghosting reagent can beobtained as a commercial product known as Reagent B of the Coulter ReticPak™. Other ghosting reagents known to those skilled in the art can beused. The ghosting process releases the hemoglobin in red blood cells,resulting in ghosted cell. The term “ghosted cell”, as used herein,refers to a red blood cell that has more that about 70% of itshemoglobin content removed. Preferably, the cell has more than 90% andeven more preferred has more than 95% of the hemoglobin removed. Inother words, the ghosted cell retains less than 30% of its originalhemoglobin. The reduction of the hemoglobin content enhances thedefinition of the reticulum to permit cytometric flow determination ofthe reticulocytes. More specifically, the reduction in hemoglobincontent of the red blood cells enables the differentiation of thereticulocytes from the mature RBC when measuring by a non-fluorescentmethod comprising light scatter and DC.

In addition to facilitating the release of hemoglobin, the ghostingprocess can also sphere the red blood cells giving the cells a moreregular shape, and thereby permitting more predictable light scattermeasurements. The native reticulocyte has an irregular shape whichproduces unpredictable light scatter information when subjected to alight beam. The sphering of the red blood cell provides reproduciblelight scatter information which forms the basis for determining thereticulocytes in the sample. In some embodiments, it might beadvantageous to combine the blood sample with a sphering agent. Thesphering agent is used in an amount effective to cause the reticulatederythrocytes and red blood cells to isovolumetrically sphere toeliminate orientation artifacts in analysis of the reticulocytes. Insome embodiments, the sphering reagent is a zwitterionic surfactantwhich isovolumetrically spheres the red blood cells. Examples ofsphering agents suitable for the present invention include, but are notlimited to, lauroamidopropylbetaine, cocoamidopropylbetaine andcocoamidosulfobetaine.

It has been previously found that the ghosting process is affected bytemperature. See, eg., U.S. Pat. No. 5,616,501, incorporated byreference herein. Temperatures below 55° F. appear to retard theghosting process and longer time periods are necessary to permit theghosting process to occur. In some embodiments, the blood sample will bemixed with the ghosting solution at a temperature of at least 55° forapproximately 30 seconds. In one embodiment, ghosting of blood samplewill be conducted at 106° F. (41° C.).

In some embodiments, the pH of the ghosting solution should be nothigher than 3.0. In one embodiment, the pH of the ghosting solution isapproximately 1.0 to 2.0. In addition, it appears that the acidicghosting solution solubilizes the hemoglobin and facilitates its removalfrom the blood cell. It has been noted that when utilizing potassiumthiocyanate, sulfuric acid is the preferred acid to be utilized in thecombination. The preferred concentration for the potassium thiocyanateis approximately from 1.0 to 6.0 grams per liter, and for the sulfuricacid is approximately from 0.7 to 3.0 grams per liter.

The osmotic pressure of the ghosting solution should be controlled sothat there is a rapid, but controlled swelling of the blood cell. Theosmotic pressure of the ghosting solution should be at least about 75milliosmoles. The osmotic pressure causes the blood cell to swell andrelease the hemoglobin within thirty (30) seconds of mixing with theghosting solution. If the osmotic pressure is less than about 75milliosmoles, then the blood cell will not retain an intact cellmembrane and will lyse. More specifically, lower osmotic pressureresults in red cells that are damaged so that reticulocyte enumerationis not reliable. If the osmotic pressure is not sufficient, the bloodcells will retain hemoglobin which will obscure reticulocytedifferentiation. In some embodiments, the osmotic pressure of theghosting solution will range from about 75 to about 110 milliosmoles. Inother embodiments, the osmotic pressure of the ghosting solution will bein the range of about 82 to about 105 milliosmoles.

Returning to FIG. 2, in step 204, the blood sample is analyzed using aparticle analyzer. In one embodiment, the particle analyzer is ahematology analyzer. For example, the blood sample, or a portion of it,is introduced into the particle analyzer. Under hydrodynamic pressure,the blood sample flows, cell by cell, through a flow cell. Within theflow cell, several parameters of the individual cells are measured. Forexample, particle analyzers using the VCS technology can perform thevolumetric sizing of a cell, conductivity of a cell, and light scatter,simultaneously for each cell. FIG. 4 is a flowchart of step 204 infurther detail, according to an embodiment of the present invention.

In step 402, the blood sample prepared in step 202, is introduced into aflow cell for analysis. In step 404, in one embodiment, the sample isinterrogated by energy from three independent sources as it flows, cellby cell, through an interrogation point in the flow cell. In step 406,the light scatter measurement is recorded for each cell event. As theRNA content decreases with the maturity of the reticulocyte, it can beexpected that the light scatter measurement decreases. Severalmeasurements of light scatter can be available, for example, and withoutlimitation, include forward light scatter measurements. Forward scattermeasures the light that passes through the cell being interrogated andthat is deflected from the axis of the beam of light. Examples offorward light scatter include, but are not limited to, lower medianangle light scatter (LMALS), upper median angle light scatter (UMALS),and low angle light scatter (LALS). The LMALS refers to light scatteredat an 9°-19° angle from the axis of the beam, UMALS refers to lightscattered at an 20°-43° angle from the axis of the beam, and LALS refersto light scattered at approximately 5.1° angle from the axis of thebeam. Another light scatter measurement, side angle light scatter(SALS), can measure light scattered at 90° angle. In some embodiments,the analyses of blood sample will include a measurement of axial lightloss (ALL). ALL is the amount of light lost at about 0° to 0.5° anglerelative to the axis of the beam.

In step 408, another measurement that is indicative of reticulocytematurity is collected. For example, in one embodiment of the presentinvention, the size of the cell can be measured. The size of the cell isknown to decrease with the maturity of the reticulocyte, in general, asthe RNA content decreases. As an example, the size of the cell, or cellvolume, can be measured using the DC measurement. The peak amplitude ofthe DC pulse is a function of cell volume. Other measurements indicativeof reticulocyte maturity, including direct or indirect ways of measuringthe volume of the cell, can be used in this step. For example,fluorescence measurement to indicate the amount of RNA in the cell, orother modes of measuring cell volume can be used. As another example,forward scatter can also be used to indicate cell size.

Returning to FIG. 2, in step 206 a reticulocyte population is identifiedfrom the entire cell event population. Scatter plots of the event data,using various axis, help identify blood cell distribution patterns. Asan example, the event data can be visualized in a scatter plot, such as,for example, FIG. 1, where the light scatter is on the x-axis and volume(DC) is on the y-axis. As indicated earlier with respect to FIG. 1, thereticulocyte population 104 can be identified separately fromerythrocytes 102, platelets 108 and white cells 106. The accuracy of thereticulocyte population is dependent particularly on how definitivelyline 130 separating the reticulocytes from the red cells can bedetermined. For example, in one embodiment, while line 130 can besuperimposed on the scatter plot 100 based on threshold light scatterand volume measurement values derived empirically from previouscollections of measurements, line 130 can fail to correctly separateerythrocytes 102 from reticulocytes (104), particularly with regard tocell events that lie in close proximity to line 130 in scatter plot 100.

Returning yet again to FIG. 2, in step 208, one or more reticulocytemeasures can be reported. In one embodiment the reticulocyte fraction isreported as the ratio of a predetermined number of regions defined onthe mapping function to the entire red blood cell population. In anotherembodiment reticulocytes can be reported as a percentage or absolutenumber. Reporting involves outputting one or more measurements to adisplay or other output device such as a computer file.

Detecting Hard-to-Ghost Cells

In one aspect, the method of the present invention allows for theaccuracy of reticulocyte detection that is reported to be improved withhaving more accurate sample data based on which to compute reticulocyteinformation. It has been observed, in some blood samples, that after theinitial ghosting process some cells remain that were either not ghostedor were only partially ghosted, i.e., “hard-to-ghost” cells. For thepurposes of the present invention, the term “hard-to-ghost cell” willrefer to a cell which has retained at least about more than 30% of itsoriginal hemoglobin content. In other words, the hard-to-ghost cell hasless than 70% of its original hemoglobin removed. Preferably, the cellhas more than 50% and even more preferred has more than 70% of theoriginal hemoglobin content. The ghosting process, for example, bycombining a hypotonic acid solution with the blood sample, is intendedto clear hemoglobin from the cells. Without ghosting or with inefficientghosting (i.e., when the cells loose less than about 30% of theirhemoglobin content), erythrocytes may not clearly differentiate fromreticulocytes. Another view of the difference from ghosted cellscompared to hard-to-ghost cells can be seen in FIG. 6 which showspopulation 610 of the hard-to-ghost cells being positioned in upperportion of the scatter plot of axial light loss versus UMALS. Whenhard-to-ghost cells are present in the blood sample, and the bloodsample is analyzed using light scatter and axial light loss, thedifferentiation of the reticulocytes from the mature red cells can failbecause the hard-to-ghost cell population is dense and is generallypositioned within the reticulocyte region. Some embodiments of thepresent involve detecting hard-to-ghost cells in the total population ofblood cells.

FIGS. 5(A) and 5(B) show the contrast presented in scatter plots of thesame event data with and without hard-to-ghost cell events, usingconventional light scatter or upper medium angle light scatter (UMALS),and DC axis. In FIG. 5(A) the scatter plot includes hard-to-ghost cellevents. The boundary 510 shows the location of a hard-to-ghost cellevent population. FIG. 5(B) shows the same event population afterhard-to-ghost cell events, including the population defined by boundary510, are removed. In both FIGS. 5(A) and 5(B), the events below boundary530 correspond to platelets and the events to the right of boundary 520correspond to white blood cells. As can be seen by the location of theboundary 510, the hard-to-ghost cell event population spans theseparation of the mature red blood cell population and the reticulocytepopulation, thereby making it difficult to clearly distinguish betweenmature red blood cells and reticulocytes. In contrast, when thehard-to-ghost cell event population is removed, as shown in FIG. 5(B), aclear boundary 511 can be defined between the mature red blood cells andreticulocytes. A visual comparison of FIGS. 5(A) and 5(B) illustratesthe difficulty in identifying and separating the mature red cells fromreticulocytes when hard-to-ghost cells are present.

In this embodiment, the axial light loss measurement enables thediscrimination of the hard-to-ghost population from the rest of thesample. It has been unexpectedly found by the inventors of the presentinvention that the same event population that cannot identify thehard-to-ghost population based on the conventionally used light scattermeasurement, can now distinguish the population using an axial lightloss measurement. For example, FIG. 6 shows the same event populationshown in FIG. 5(A), but using axial light loss (ALL) and UMALS insteadof the conventional DC and UMALS. Using ALL, hard-to-ghost cell eventscan be clearly identified, as shown by the area within the boundary 610.

FIGS. 7(A-C) illustrate the hard-to-ghost cell event removal of anotherblood sample using ALL in an embodiment of the present invention.Scatter plot 710 shows the generally used UMALs and DC. In scatter plot710, hard-to-ghost cells are present (as shown within boundary 711), butcannot be clearly distinguished from other red blood cells. However,when the same data is shown in scatter plot 720, having axial light loss(ALL) and UMALS as axis, the ability to detect hard-to-ghost cells isvastly improved. Based on ALL, the hard-to-ghost population 721 isclearly discernible from the other event populations.

In one embodiment of the present invention, the cell eventscorresponding to the hard-to-ghost population can be filtered-out, andthe remaining cell events can be displayed in scatter plot, for examplesuch as 730, using UMALS axis and DC axis. Filtering-out cell eventscorresponding to the hard-to-ghost population can be accomplished bygating the hard-to-ghost population either, automatically based on, forexample, threshold ALL and UMALS values determined empirically, or withmanual operator assistance. A visual comparison of scatter plots 730 and710 illustrates the clearer distinction between the mature red bloodcell population to the left of boundary 731 and the reticulocytepopulation to the right of boundary 731.

As shown in FIG. 6 (specifically the area within boundary 610) and FIGS.7(A-C) (specifically the area within boundary 721), when using ALL,hard-to-ghost cells can be identified as a distinct population fromother populations such as mature red blood cells, reticulocytes,platelets and white blood cells. The hard-to-ghost cells generallydisplay a higher ALL than other blood cell types except for white bloodcells. White blood cells can be distinguished due to their high lightscatter measurements relative to other blood cell types. The high ALL ofthe hard-to-ghost cell population can be attributed to the relativelyhigh light absorption of hemoglobin. At a laser wavelength of 488 nm(the wavelength used in the particle analyzer that yielded results shownin FIGS. 5(A), 5(B), 6 and 7(A-C)) hemoglobin displays very high opticalabsorption that leads to a high level of ALL. In general, hemoglobinshows increased absorption of light when the light is between 400-500 nmwavelength.

Detection of the hard-to-ghost cells in a blood sample being analyzedcan be accomplished by the embodiment of the present invention shown inFIG. 8. In FIG. 8, step 202 of FIG. 2 is further dissected to includesteps to detect hard-to-ghost cells. In step 802, a prepared bloodsample, i.e., a sample having been ghosted and stained, can beintroduced to a flow cell for analysis. In step 804, the sample isinterrogated, cell by cell, using measurements including a light beam asexplained with respect to FIG. 2 above. In step 806, the ALL measurementis collected, along with one or more light scatter measurements in step810. Descriptions of the light scatter measurement can be found abovewith respect to FIG. 2.

In one embodiment, once the hard-to-ghost cells are detected, this eventdata can be used to more accurately analyze reticulocytes. For example,the hard-to-ghost cell population can be filtered out using the ALLvalues of the reticulocyte events, as in step 812. In this embodiment,the event data will be available for further analysis for determiningreticulocyte information or any other red cell information, as in step814. In general, the removal of the hard-to-ghost cell event populationwould increase the accuracy of most parameters reported concerning redblood cells and/or reticulocytes. Calculation and reporting ofreticulocyte information is described above with respect to FIG. 2.

Enumerating Hard-to-Ghost Cells

One aspect of the present invention is concerned with enumerating thehard-to-ghost cells in the blood sample. It has been unexpectedlydiscovered by the inventors of the present invention that there exists acorrelation between the hard-to-ghost cell population in a blood sampleand a blood pathology. Specifically, it has been found that the numberof hard-to-ghost cells is increased in analyzed blood samples collectedfrom patients suffering from various diseases, examples of whichinclude, but are not limited to, diseases such as hemoglobinopathies,(e.g., sickle cell anemia and Thalassemia), hematological malignancies(e.g., leukemias and lymphomas), clotting and bleeding disorders, aswell as HIV/AIDS, malignant tumors, and autoimmune disorders. Inaddition, further information can be obtained about these diseases whencomparing the position of the hard-to-ghost cells in the scattergram tonormal samples. Returning to FIG. 8, following the detection,hard-to-ghost cells can be enumerated, as in step 813. Counting orenumerating of cells is a well-established technique for well-definedcell populations, such as the presently defined hard-to-ghost cells. Inone embodiment the hard-to-ghost fraction is reported as the ratio ofhard-to-ghost cells to the entire red blood cell population. In anotherembodiment hard-to-ghost cells can be reported as a percentage orabsolute number. Said value can be used as a research use only (RUO)parameter, or can be developed into an in vitro diagnostic (IVD)parameter. FIGS. 10 (A-C) illustrate the difference in size ofhard-to-ghost cell populations 1010 in blood samples derived from ahealthy individuals (FIG. 10(A)) and from patients suffering from sicklecell anemia (FIG. 10(B)) and Thalassemia (FIG. 10(C)). As illustrated bythe FIGS. 10(A) and 11, the % hard-to-ghost cells of a total RBCpopulation is negligible, i.e., less than about 0.01% in blood samplesdonated by healthy individuals. It has also been determined that bloodsamples from patients suffering from a number of certain pathologiescontain an increased population of hard-to-ghost cells (illustrated inFIG. 12). Such pathologies include renal failure, liver cancer, HIV,sickle cell anemia, and thalassemia. The % hard-to-ghost cells of atotal RBC population in a blood sample of a patient with a certaindiagnosed disease state is increased at least 10-fold from thehard-to-ghost cell population size of a healthy individual. In someblood samples, the hard-to-ghost cell population of a patient sufferingfrom a disease or disorder is at least 100-fold greater than that of ahealthy individual. The discovery of this trend by the inventors of thepresent invention can be useful in determining existence of abnormalpopulation of hard-to-ghost cells, which may further be related to apresence of certain pathologies.

Alternate methods can be employed to enumerate hard-to-ghost cells. Moreparticularly, one skilled in the art can analyze a blood sample byghosting the sample and measuring cell by cell hemoglobin of the bloodcell sample using light scatter measurement as known to those skilled inthe art. Those cells which have greater than 30% of the originalhemoglobin are considered hard-to-ghost cells. In other words, thehard-to-ghost cells will have greater light scatter than a ghosted cellsin the scattergram. In this alternate method, one skilled in the artcould also employ a fluorescent dye to differentiate the reticulocytesfrom the hard-to-ghost cells.

It will be understood by a skilled artisan that the environments inwhich this invention can be practiced, such as flow cytometers andhematology analyzers, can be programmed to report a numerical value forhard-to-ghost cell population. This numerical value can be correlated toa biochemical and/or a physiological state of an individual. Forexample, a threshold value can be set for % hard-to-ghost cell of totalred blood cells in a blood sample that corresponds to the number ofhard-to-ghost cells present in a healthy individual. When a number ofhard-to-ghost cells in a blood sample derived from a patient exceedssuch threshold value, a disease state can be suspected and the bloodsample can be reported, warranting further diagnostic evaluation of thepatient. A physician assessing the blood count result will determine theappropriate further testing based on patient's symptoms, general healthstatus, disease or disorder, gender, and age. In one embodiment, a bloodsample can be reported for further evaluation if % hard-to-ghost cell ina blood sample exceeds the threshold value by at least 10-fold. Inanother embodiment, a blood sample can be reported for furtherevaluation if % hard-to-ghost cell in a blood sample exceeds thethreshold value by at least 100-fold.

System to Determine Blood Cell Information

FIG. 9 shows a system to analyze blood samples according to anembodiment of the present invention. A particle analyzer 910 is coupledusing link 940 to a computer 901. Computer 901 is optionally coupledusing link 950 to a display 920, and/or an external storage device 921.Computer 901 can include a processor 902, a memory 903, an internalstorage 904, an input module 905, an output module 906, and areticulocyte module 907. Reticulocyte module 907 can include a detectormodule 961, an analyzer module 963, a differentiator module 965, and areporter module 967.

Particle analyzer 910 can include a hematology analyzer, flow cytometer,or similar device that is capable of interrogating a blood sample withthe use of a beam of light. A blood sample is prepared an input toparticle analyzer 910 for analysis. The event data generated by particleanalyzer 910 is communicated to computer 901, over the link 940. Link940 can be a device-internal connection such as peripheral componentinterconnect (PCI) bus, or a network connection. The events generated bythe analysis of blood samples in particle analyzer 910 can becommunicated to computer 901 in real-time or in batch-mode.

The event data, subsequent to any processing within computer 901, isthen presented to a user on display 920, or stored in external storagedevice 921. For example, scatter plots generated by processing withincomputer 901 can be presented to the user using display 920. Processedevent data can also be stored for later analysis and display. Externalstorage device 921 can include a hard drive, or other type of portablestorage.

Processor 902 can execute instructions that enable the processing ofmodules 905, 906 and 907. Internal memory 903 provides the temporarymemory required for such processing, and internal storage 904 canprovide for the temporary or intermediate storage of data and resultsassociated with such processing. Internal storage 904 can also storecontrol logic based on instructions and/or program code of modulesincluding the component modules of reticulocyte module 907, in the formsincluding computer readable program code.

Input module 905 receives the event data generated by particle analyzer910. Input module 905 can include any processing that is required totransform the input event data from particle analyzer 910, to a formatunderstood by reticulocyte module 907. Output module 906 collects theevent data processed by reticulocyte module 907, performs any conversionnecessary, and outputs to either display 920 or storage 920, using link950. Link 950 can be an device-internal connection such as PCI, or anetwork connection. Display 920 can be a display device that iscustomized for the viewing of particle analyzer data, a generic display,or any other means capable of outputting results of the particleanalysis.

The detector module 961 can include the instructions for determiningmeasurements or parameters of cell events as they pertain to sidescatter including UMALS, forward scatter, axial light loss, and DC. Notethat every embodiment of the present invention may not have access toall of the measurements above. There may be some configuration requiredon particle analyzer 910 to enable the collection of all of the abovemeasurements.

Analyzer module 963 includes the instructions for identifying thereticulocyte population and/or a hard-to-ghost cell population, andisolating that population from other types of blood cells. In anotherembodiment, analyzer module 963 can include instructions to filter-outthe cell events corresponding to hard-to-ghost cells, as explainedabove. In yet another embodiment, analyzer module 963 can includeinstructions for enumerating the hard-to-ghost cell population.

Differentiator module 965 can include instructions that cause thecomputer to determine the immature reticulocyte information of thesample being analyzed. For example, the reticulocyte event populationidentified using module 963, may now be investigated using both, thelight scatter measurement as well as a second reticulocyte maturitymeasurement such as volume, to differentiate the mature from theimmature reticulocytes.

Reporter module 967 includes the instruction enabling computer 901 todisplay scatter plots to display 920, and also to report usefulquantifications of the reticulocytes in the blood sample. Thereticulocyte fraction or the reticulocyte percentage are somequantifications that can be reported by reporter module 967. Reportermodule 967 can also include instructions to report information abouthard-to-ghost cell populations.

In this disclosure, methods were disclosed that can improve the accuracyof blood sample analysis through measures such as the reticulocytefraction and hard-to-ghost cells. The disclosed methods yieldsubstantial improvements over the current methods and can lead tosignificant improvements in the detection and treatment of a number ofblood pathologies. Persons skilled in the art will understand that thetechniques disclosed herein can be applicable for cell types other thanerythrocytes as described here.

The foregoing description of the invention has been presented forpurposes of illustration and description. It is not intended to beexhaustive or to limit the invention to the precise form disclosed, andother modifications and variations may be possible in light of the aboveteachings. The embodiment was chosen and described in order to bestexplain the principles of the invention and its practical application tothereby enable others skilled in the art to best utilize the inventionin various embodiments and various modifications as are suited to theparticular use contemplated. It is intended that the appended claims beconstrued to include other alternative embodiments of the inventionexcept insofar as limited by the prior art.

What is claimed is:
 1. A method of detecting hard-to-ghost cells in ablood sample comprising: (a) mixing the blood sample with a ghostingreagent to remove hemoglobin from red blood cells, thereby generating aghosted blood sample; (b) evaluating the ghosted blood sample in acytometric flow cell by a detection comprising an axial light lossmeasurement, thereby generating event data; and (c) identifyinghard-to-ghost cells using axial light loss measurement of the eventdata.
 2. The method of claim 1, wherein the identification of thehard-to-ghost cells using the axial light loss measurement comprisescomparing the axial light loss measurement against a first threshold anda light scatter measurement against a second threshold, wherein thehard-to-ghost cells are identified as having an axial light lossmeasurement greater than the first threshold and a light scattermeasurement lower than the second threshold.
 3. The method of claim 2,wherein the light scatter measurement comprises upper median angle lightscatter (UMALS), lower median angle light scatter (LMALS), and low anglelight scatter (LALS).
 4. The method of claim 3, wherein the lightscatter measurement is UMALS.
 5. The method of claim 1, furthercomprising collecting direct current impedance measurements.
 6. A methodof enumerating hard-to-ghost cells in a blood sample comprising: (a)mixing the blood sample with a ghosting reagent to remove hemoglobinfrom red blood cells, thereby generating a ghosted blood sample; (b)evaluating the ghosted blood sample in a cytometric flow cell by adetection comprising an axial light loss measurement, thereby generatingevent data; (c) identifying hard-to-ghost cells using axial light lossmeasurement of the event data; (d) enumerating the hard-to-ghost cellpopulation using the axial light loss measurement; and (e) reporting thehard-to-ghost cell population in the blood sample,
 7. The method ofclaim 6, wherein reporting the hard-to-ghost cell population includesreporting a ratio of the hard-to-ghost cell population to total redblood cells.
 8. The method of claim 6, wherein reporting thehard-to-ghost cell population includes reporting a % hard-to-ghost cellsof total red blood cell population.
 9. A method of detecting an abnormalpopulation of hard-to-ghost cells in a patient sample, comprising: (a)mixing a blood sample from the patient with a ghosting reagent to removehemoglobin from red blood cells, thereby generating a ghosted bloodsample; (b) evaluating the ghosted blood sample in a cytometric flowcell by a detection comprising an axial light loss measurement, therebygenerating event data; (c) identifying hard-to-ghost cells using axiallight loss measurement of the event data; (d) enumerating thehard-to-ghost cell population using the axial light loss measurement;and (e) determining existence of abnormal population of hard-to-ghostcells when the number of hard-to-ghost cells exceeds a threshold value.10. The method of claim 9, wherein the abnormal population ofhard-to-ghost cells is associated with hemoglobinopathy.
 11. The methodof claim 10, wherein hemoglobinopathy comprises sickle cell anemia orthalassemia.
 12. A method of analyzing a blood sample, comprising: (a)mixing the blood sample with a ghosting reagent to remove hemoglobinfrom red blood cells, thereby generating a ghosted blood sample; (b)measuring the ghosted blood sample in a cytometric flow cell by adetection comprising an axial light loss measurement to generate eventdata; (c) identifying a hard-to-ghost cell population using the eventdata, based on said axial light loss measurement; (d) filtering-out thehard-to-ghost cell population from said event data; and (e) analyzingthe event data without the hard-to-ghost cell population to identifyblood cell distribution patterns.